EP3690717C0 - Lernverfahren und lernvorrichtung sowie prüfverfahren und prüfvorrichtung zur erkennung von parkplätzen durch verwendung von punktregressionsergebnissen und beziehungen zwischen punkten zur bereitstellung eines autoparksystems - Google Patents
Lernverfahren und lernvorrichtung sowie prüfverfahren und prüfvorrichtung zur erkennung von parkplätzen durch verwendung von punktregressionsergebnissen und beziehungen zwischen punkten zur bereitstellung eines autoparksystemsInfo
- Publication number
- EP3690717C0 EP3690717C0 EP20152475.8A EP20152475A EP3690717C0 EP 3690717 C0 EP3690717 C0 EP 3690717C0 EP 20152475 A EP20152475 A EP 20152475A EP 3690717 C0 EP3690717 C0 EP 3690717C0
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- 238000012360 testing method Methods 0.000 title 2
- 238000000034 method Methods 0.000 title 1
Classifications
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
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- G06N3/00—Computing arrangements based on biological models
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- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
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- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/06—Automatic manoeuvring for parking
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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- G05D1/0088—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
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- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
- G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
- G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
- G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
- G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
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- G06V10/457—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by analysing connectivity, e.g. edge linking, connected component analysis or slices
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- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
- G06V20/586—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of parking space
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
- G08G1/141—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
- B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
- B60W2420/403—Image sensing, e.g. optical camera
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Y—INDEXING SCHEME RELATING TO ASPECTS CROSS-CUTTING VEHICLE TECHNOLOGY
- B60Y2300/00—Purposes or special features of road vehicle drive control systems
- B60Y2300/06—Automatic manoeuvring for parking
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- G—PHYSICS
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- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
Landscapes
- Engineering & Computer Science (AREA)
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Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201962798535P | 2019-01-30 | 2019-01-30 | |
US16/731,077 US10628688B1 (en) | 2019-01-30 | 2019-12-31 | Learning method and learning device, and testing method and testing device for detecting parking spaces by using point regression results and relationship between points to thereby provide an auto-parking system |
Publications (3)
Publication Number | Publication Date |
---|---|
EP3690717A1 EP3690717A1 (de) | 2020-08-05 |
EP3690717B1 EP3690717B1 (de) | 2023-12-13 |
EP3690717C0 true EP3690717C0 (de) | 2023-12-13 |
Family
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Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
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EP20152475.8A Active EP3690717B1 (de) | 2019-01-30 | 2020-01-17 | Lernverfahren und lernvorrichtung sowie prüfverfahren und prüfvorrichtung zur erkennung von parkplätzen durch verwendung von punktregressionsergebnissen und beziehungen zwischen punkten zur bereitstellung eines autoparksystems |
Country Status (5)
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US (1) | US10628688B1 (de) |
EP (1) | EP3690717B1 (de) |
JP (1) | JP6923960B2 (de) |
KR (1) | KR102373456B1 (de) |
CN (1) | CN111507460B (de) |
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WO2018176000A1 (en) | 2017-03-23 | 2018-09-27 | DeepScale, Inc. | Data synthesis for autonomous control systems |
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US11893393B2 (en) | 2017-07-24 | 2024-02-06 | Tesla, Inc. | Computational array microprocessor system with hardware arbiter managing memory requests |
US11157441B2 (en) | 2017-07-24 | 2021-10-26 | Tesla, Inc. | Computational array microprocessor system using non-consecutive data formatting |
US11409692B2 (en) | 2017-07-24 | 2022-08-09 | Tesla, Inc. | Vector computational unit |
US11561791B2 (en) | 2018-02-01 | 2023-01-24 | Tesla, Inc. | Vector computational unit receiving data elements in parallel from a last row of a computational array |
US11215999B2 (en) | 2018-06-20 | 2022-01-04 | Tesla, Inc. | Data pipeline and deep learning system for autonomous driving |
US11361457B2 (en) | 2018-07-20 | 2022-06-14 | Tesla, Inc. | Annotation cross-labeling for autonomous control systems |
US11636333B2 (en) | 2018-07-26 | 2023-04-25 | Tesla, Inc. | Optimizing neural network structures for embedded systems |
US11562231B2 (en) | 2018-09-03 | 2023-01-24 | Tesla, Inc. | Neural networks for embedded devices |
EP3864573A1 (de) | 2018-10-11 | 2021-08-18 | Tesla, Inc. | Systeme und verfahren zum trainieren von maschinenmodellen mit erweiterten daten |
US11196678B2 (en) | 2018-10-25 | 2021-12-07 | Tesla, Inc. | QOS manager for system on a chip communications |
US11816585B2 (en) | 2018-12-03 | 2023-11-14 | Tesla, Inc. | Machine learning models operating at different frequencies for autonomous vehicles |
US11537811B2 (en) | 2018-12-04 | 2022-12-27 | Tesla, Inc. | Enhanced object detection for autonomous vehicles based on field view |
US11610117B2 (en) | 2018-12-27 | 2023-03-21 | Tesla, Inc. | System and method for adapting a neural network model on a hardware platform |
US10997461B2 (en) | 2019-02-01 | 2021-05-04 | Tesla, Inc. | Generating ground truth for machine learning from time series elements |
US11150664B2 (en) | 2019-02-01 | 2021-10-19 | Tesla, Inc. | Predicting three-dimensional features for autonomous driving |
US11567514B2 (en) | 2019-02-11 | 2023-01-31 | Tesla, Inc. | Autonomous and user controlled vehicle summon to a target |
US10956755B2 (en) | 2019-02-19 | 2021-03-23 | Tesla, Inc. | Estimating object properties using visual image data |
US11482015B2 (en) * | 2019-08-09 | 2022-10-25 | Otobrite Electronics Inc. | Method for recognizing parking space for vehicle and parking assistance system using the method |
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CN111508269B (zh) * | 2020-04-23 | 2021-05-18 | 深圳智优停科技有限公司 | 一种基于图像识别的开放式停车位车辆判别方法与装置 |
US20210114586A1 (en) * | 2020-12-23 | 2021-04-22 | Ralf Graefe | Autonomous driving vehicle parking detection |
CN113525357B (zh) * | 2021-08-25 | 2022-12-09 | 吉林大学 | 自动泊车决策模型优化系统及方法 |
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KR101188588B1 (ko) * | 2008-03-27 | 2012-10-08 | 주식회사 만도 | 모노큘러 모션 스테레오 기반의 주차 공간 검출 장치 및방법 |
JP5309891B2 (ja) * | 2008-10-27 | 2013-10-09 | 三菱自動車工業株式会社 | 駐車支援装置 |
KR101583998B1 (ko) * | 2014-10-17 | 2016-01-19 | 현대자동차주식회사 | 주차지원장치 및 방법 |
US20180356492A1 (en) * | 2015-06-16 | 2018-12-13 | Michael Hamilton | Vision based location estimation system |
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CN106874551B (zh) * | 2017-01-11 | 2020-12-01 | 成都信息工程大学 | 一种基于三阶反正切函数模型的平行泊车方法 |
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TWI651697B (zh) * | 2018-01-24 | 2019-02-21 | National Chung Cheng University | 停車場空位偵測方法及其偵測模型建立方法 |
US11501572B2 (en) * | 2018-03-26 | 2022-11-15 | Nvidia Corporation | Object behavior anomaly detection using neural networks |
US10789487B2 (en) * | 2018-04-05 | 2020-09-29 | Here Global B.V. | Method, apparatus, and system for determining polyline homogeneity |
CN108592915A (zh) * | 2018-04-19 | 2018-09-28 | 京东方科技集团股份有限公司 | 导航方法、购物车及导航系统 |
US11334960B2 (en) * | 2018-06-08 | 2022-05-17 | Uatc, Llc | Systems and methods for pipelined processing of sensor data using hardware |
-
2019
- 2019-12-31 US US16/731,077 patent/US10628688B1/en active Active
-
2020
- 2020-01-13 KR KR1020200004512A patent/KR102373456B1/ko active IP Right Grant
- 2020-01-17 EP EP20152475.8A patent/EP3690717B1/de active Active
- 2020-01-22 JP JP2020008617A patent/JP6923960B2/ja active Active
- 2020-01-23 CN CN202010077088.2A patent/CN111507460B/zh active Active
Also Published As
Publication number | Publication date |
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US10628688B1 (en) | 2020-04-21 |
CN111507460A (zh) | 2020-08-07 |
JP2020123343A (ja) | 2020-08-13 |
JP6923960B2 (ja) | 2021-08-25 |
KR102373456B1 (ko) | 2022-03-14 |
KR20200094652A (ko) | 2020-08-07 |
CN111507460B (zh) | 2023-07-28 |
EP3690717B1 (de) | 2023-12-13 |
EP3690717A1 (de) | 2020-08-05 |
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